SuperAnnotate AI

SuperAnnotate provides an end-to-end data infrastructure platform designed to create, manage, and evaluate high-quality training datasets for artificial intelligence applications. The company was founded in August 2018 by brothers Tigran and Vahan Petrosyan. The foundation for the company's technology stemmed from Vahan's PhD research in image segmentation at Sweden's KTH Royal Institute of Technology, while Tigran was pursuing his PhD in Biomedical Imaging and Photonics at ETH Zurich. Both brothers left their doctoral programs to establish the company. The firm's headquarters are in San Francisco, California. Its journey began with acceptance into Berkeley's SkyDeck accelerator program in January 2019. SuperAnnotate has secured significant funding through several rounds, including a $3 million Seed round in June 2020, a $14.5 million Series A in July 2021, and a Series B round that reached a total of $50 million after an initial $36 million in November 2024 was extended by a further $13.5 million from Dell Technologies Capital. Notable investors include NVIDIA, Databricks Ventures, Cox Enterprises, and Lionel Messi’s Play Time VC. SuperAnnotate's business model combines a Software as a Service (SaaS) platform with managed services, catering primarily to an enterprise B2B market. Clients include companies like Databricks, IBM, ServiceNow, Canva, and Motorola Solutions. The platform is designed to unify the AI pipeline, supporting the creation, curation, and evaluation of datasets for computer vision, natural language processing (NLP), and large language models (LLMs). It offers a suite of tools for workflow automation, team management, and quality control, which can be integrated with clients' existing data sources and model training pipelines. A key feature is its support for multimodal data, allowing for the annotation of images, video, text, and audio within a single interface. In addition to its software, SuperAnnotate provides access to a global network of vetted data annotation experts who can be hired for specific projects, offering a managed workforce solution to scale data labeling operations. Keywords: AI data platform, data annotation, training data, dataset creation, dataset management, model evaluation, computer vision, natural language processing, LLM, multimodal AI, human-in-the-loop, reinforcement learning, data labeling, AI development, machine learning, data infrastructure, AI pipeline, workflow automation, quality assurance, data curation, image segmentation, video annotation, text annotation, audio annotation, GenAI, enterprise AI